Data Science for Future-Proof Transport Planning

Inaugural Lecture
Robin Lovelace
r.lovelace@leeds.ac.uk

University of Leeds

May 8, 2025

Contents

Past

  • Before Leeds
  • Leeds

Present

  • Transport Data Science
  • Biclar
  • Network Planning Tool

FUTURE

My journey

Figure 1: Places I have lived for 1+ years

Where I grew up

Photo: 2025 from Google Street View

Where I’m from

Figure 2: Places where I spent a lot of time in Herefordshire
  • Scholarship to study Environmental Science and Management

Influential book “SEWTHA”, freely available at withouthotair.com (MacKay 2009)

Blog post in The Oil Drum

Engineers Without Borders (EWB)

Wind turbine group

Finished wind turbine

Interest in sustainable transport

Cargo bike and bike trailers in action, June 2010

My thesis

Source: https://etheses.whiterose.ac.uk/id/eprint/5027/

Spatial microsimulation

First proper job (🙏Mark Birkin) and first Leeds-based paper (Lovelace et al. 2014)

Side projects: Cycling uptake work for CyclingUK

Source: CyclingUK (formerly CTC) response to government’s Cycling Delivery Plan consultation, available online at cyclinguk.org.

Work commissioned by CyclingUK (previously CTC)

Work on the economic benefits of cycling nationwide with James Woodcock and Fiona Crawford (Crawford and Lovelace 2015)

Propensity to Cycle Tool (www.pct.bike)

Source: article in practitioner magazine (Lovelace 2016).

First Propensity to Cycle Tool paper published in an academic journal (Lovelace et al. 2017)

From research to web tool

Research impact

Source: leeds.ac.uk front page, 2017-03-17

4* Research Excellence Framework (REF) case study

Source: results2021.ref.ac.uk (Lovelace et al. 2023)

Internship in No. 10 Downing Street

Fellowship in collaboration with 10 Downing Street, ONS, Data Science Campus, ADRUK, ESRC from November 2021 until April 2023

Source: Press Release “No.10 Data Science Fellowship”

Source: “Packaging Code and Data for Reproducible Research: A Case Study of Journey Time Statistics.” Environment and Planning B Botta et al. (2024).

Active Travel England

Department for Transport's Data Science for Transport conference

2 year contract in the Civil Service from January 2023

My roles:

  • Recruit the team
  • Lead Data Scientist
  • Projects: plan.activetravelengland.gov.uk (formerly ATIP), SchoolRoutes

Source: photo taken May 2023 at the Department for Transport’s Data Science for Transport conference

Active Travel England - Alan Turing Institute grant

Photo credit: Danny Williams

Massive thanks to

Katy

Kit

Rosa

My current role

  • Professor of Transport Data Science
  • Work with government
  • Focus on impact
  • R package developer and data scientist
  • New methods for more reproducible, data-driven and participatory transport planning

What is Transport Data Science?

(I-)Reproducibility

Reproducibility is a continuous variable (Peng 2011)

Reproducible research

Why make your research (more) reproducible?

Source: Raff (2023)

  • Scientific rigour
  • Benefits to your future self
  • Benefits to others
  • Huge increase in potential for impact

Why not make your research reproducible?

  • Time

  • Know-how

  • Lack of permission

  • Software is not open

  • Data is not open access

  • Someone might use it in unethical ways

  • Someone might “steal” the work

Example of fully reproducible research

Lovelace, Tennekes, and Carlino (2022)

Reproducibility and generalisability

Illustration of the ClockBoard zoning system used to visualize a geographically dependendent phenomena: air quality, measured in mass of PM10 particles, measured in micrograms per cubic meter, from the London Atmospheric Emissions Inventory (LAEI). The facets show the data in spatial grid available from the LAEI, facet Am and aggregated to London boroughs B, to ClockBoard zones covering all the input data shown in C, and ClockBoard zones clipped by the administrative boundary of Greater London in D.

Application: road traffic casualties

International comparisons

Premise: A key reason for reproducibility is generalisability.

Open source software and open access tools

Case study: mobile telephone data in Spain

Don’t reinvent the wheel

Before

options(timeout = 600) # 10 minutes
u1 = "https://movilidad-opendata.mitma.es/estudios_basicos/por-distritos/viajes/ficheros-diarios/2024-03/20240301_Viajes_distritos.csv.gz"
f1 = basename(u1)
if (!file.exists(f1)) {
  download.file(u1, f1)
}
drv = duckdb::duckdb("daily.duckdb")
con = DBI::dbConnect(drv)
od1 = duckdb::tbl_file(con, f1)

Credit: Egor Kotov

remotes::install_github("Robinlovelace/spanishoddata")
od_multi_list = get_od(date_regex = "2024030[1-7]")
# ...
n_per_hour |>
  ggplot(aes(x = Time, y = Trips)) +
  geom_line(aes(colour = Day)) +
  labs(title = "Number of trips per hour over 7 days")

Building/linking-up-with communities

The package has been onboarded to rOpenSpain public benefit data science community (see ropenspain.github.io)

Cross-language collaboration

Source: https://github.com/dabreegster/odjitter

From open source to open access

“In essence ‘open access’ goes beyond ‘open source’ in that users are not only given the option of viewing (potentially indecipherable) source code, but are encouraged to do so, with measures taken in the software itself, and the community that builds it, to make it more user-friendly.””

Source: (Lovelace, Parkin, and Cohen 2020)

References

Botta, Federico, Robin Lovelace, Laura Gilbert, and Arthur Turrell. 2024. “Packaging Code and Data for Reproducible Research: A Case Study of Journey Time Statistics.” Environment and Planning B: Urban Analytics and City Science 52 (4): 1002–13. https://doi.org/10.1177/23998083241267331.
Crawford, F., and R. Lovelace. 2015. “The Benefits of Getting England Cycling.” http://www.ctc.org.uk/sites/default/files/1501_fcrawford-rlovelace_economic-cycle-reformatted.pdf.
Lovelace, Robin. 2016. “Mapping Out the Future of Cycling.” Get Britain Cycling 5: 2224. http://eprints.whiterose.ac.uk/100080/.
Lovelace, Robin, M Birkin, Joseph Talbot, and Malcolm Morgan. 2023. “Cycle Network Policy, Planning and Investment Transformed by the Propensity to Cycle Tool.” https://results2021.ref.ac.uk/impact/847d1191-7f25-46ba-a399-b481125edc8f?page=1.
Lovelace, Robin, Anna Goodman, Rachel Aldred, Nikolai Berkoff, Ali Abbas, and James Woodcock. 2017. “The Propensity to Cycle Tool: An Open Source Online System for Sustainable Transport Planning.” Journal of Transport and Land Use 10 (1). https://doi.org/10.5198/jtlu.2016.862.
Lovelace, Robin, Nick Malleson, Kirk Harland, and Mark Birkin. 2014. “Geotagged Tweets to Inform a Spatial Interaction Model: A Case Study of Museums.” https://doi.org/10.48550/ARXIV.1403.5118.
Lovelace, Robin, John Parkin, and Tom Cohen. 2020. “Open Access Transport Models: A Leverage Point in Sustainable Transport Planning.” Transport Policy 97 (October): 47–54. https://doi.org/10.1016/j.tranpol.2020.06.015.
Lovelace, Robin, Martijn Tennekes, and Dustin Carlino. 2022. “ClockBoard: A Zoning System for Urban Analysis.” Journal of Spatial Information Science, no. 24 (June): 63–85. https://doi.org/10.5311/JOSIS.2022.24.172.
MacKay, David J C. 2009. Sustainable Energy Without the Hot Air. Cambridge: UIT.
Peng, Roger D. 2011. “Reproducible Research in Computational Science.” Science (New York, N.y.) 334 (6060): 1226–27. https://doi.org/10.1126/science.1213847.
Raff, Edward. 2023. “Does the Market of Citations Reward Reproducible Work?” In, 8996. ACM REP ’23. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3589806.3600041.